Comparison of behavior analysis sandboxes using various machine learning algorithms for malware detection

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Comparison of behavior analysis sandboxes using various machine learning algorithms for malware detection

the overall best classification performance goes to Random Forest with arnrecall (true positive rate - Personal Name;

Malware or malicious software has grown rapidly and presented huge information secu-rnrity challenges to a computer system. Many of Anti-Virus (AV) products failed to detectrnnew or unknown malware

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B01926 (Rack Thesis) Available

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Series Title: -
Call Number: 1926
Publisher: : Swiss German University., 2015
Collation: -
Language: English
ISBN/ISSN: -
Classification: NONE
Content Type: -
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Subject(s): a precision (positive predictive value) of 98.23%
Specific Detail Info: -
Statement of Responsibility: which provide an isolated environment for analyzing behavior ofrnthe malware. This paper presents the comparison of 2 behavior analysis sandboxes forrntheir accuracy in detecting malware using several

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